Abstract: A versatile intelligent fault diagnosis (IFD) method for a distribution grid integrating renewable energy resources is described. Advanced signal processing techniques extract useful features from recorded three-phase current signals, which are input to a multilayer perceptron neural networks (MLP-NN) to diagnose i.e., to detect, classify, identify the feeder branch, and locate the faults. Once a fault is detected, classified and located, a grid operator may adjust grid parameters or dispatch a technician to correct the fault. The IFD method is independent of load demand, renewable energy generation, and fault information (resistance and inception angle) uncertainties, as well as measurement noise.

Abstract: A composite phase-change material containing a hierarchically porous Ca1-xMgxCO3 and having pores loaded with a phase change material is described. The heat storage material has a latent heat of melting 123 to 221 J/g, a latent heat of freezing of 107 to 201 J/g, and a thermal conductivity of 0.22 to 0.45 W·m?1·K?1. The phase change material may be polyethylene glycol, and the polyethylene glycol does not leak from the pores of the hierarchically porous Ca1-xMgxCO3 when heating or cooling over phase transitions.

Abstract: A composite phase-change material containing a hierarchically porous Ca1-xMgxCO3 and having pores loaded with a phase change material is described. The heat storage material has a latent heat of melting 123 to 221 J/g, a latent heat of freezing of 107 to 201 J/g, and a thermal conductivity of 0.22 to 0.45 W·m?1·K?1. The phase change material may be polyethylene glycol, and the polyethylene glycol does not leak from the pores of the hierarchically porous Ca1-xMgCO3 when heating or cooling over phase transitions.

Abstract: A versatile intelligent fault diagnosis (IFD) method for a distribution grid integrating renewable energy resources is described. Advanced signal processing techniques extract useful features from recorded three-phase current signals, which are input to a multilayer perceptron neural networks (MLP-NN) to diagnose i.e., to detect, classify, identify the feeder branch, and locate the faults. Once a fault is detected, classified and located, a grid operator may adjust grid parameters or dispatch a technician to correct the fault. The IFD method is independent of load demand, renewable energy generation, and fault information (resistance and inception angle) uncertainties, as well as measurement noise.